{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "An example of node classification on a homogeneous graph using the `Node2Vec` representation learning algorithm. The example uses components from the `stellargraph`, `Gensim`, and `scikit-learn` libraries.\n",
    "\n",
    "**Note:** For clarity of exposition, this notebook forgoes the use of standard machine learning practices such as `Node2Vec` parameter tuning, node feature standarization, data splitting that handles class imbalance, classifier selection, and classifier tuning to maximize predictive accuracy. We leave such improvements to the reader.\n",
    "\n",
    "<a name=\"refs\"></a>\n",
    "### References\n",
    "\n",
    "[1] Node2Vec: Scalable Feature Learning for Networks. A. Grover, J. Leskovec. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016. ([link](https://snap.stanford.edu/node2vec/))\n",
    "\n",
    "[2] Distributed representations of words and phrases and their compositionality. T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean.  In Advances in Neural Information Processing Systems (NIPS), pp. 3111-3119, 2013. ([link](https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf))\n",
    "\n",
    "[3] Gensim: Topic modelling for humans. ([link](https://radimrehurek.com/gensim/))\n",
    "\n",
    "[4] scikit-learn: Machine Learning in Python ([link](http://scikit-learn.org/stable/))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.linear_model import LogisticRegressionCV\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "import os\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from stellargraph.data import BiasedRandomWalk\n",
    "from stellargraph import StellarGraph\n",
    "from stellargraph import datasets\n",
    "from IPython.display import display, HTML\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "The Cora dataset consists of 2708 scientific publications classified into one of seven classes. The citation network consists of 5429 links. Each publication in the dataset is described by a 0/1-valued word vector indicating the absence/presence of the corresponding word from the dictionary. The dictionary consists of 1433 unique words."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = datasets.Cora()\n",
    "display(HTML(dataset.description))\n",
    "dataset.download()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Largest subgraph statistics: 2485 nodes, 5069 edges\n"
     ]
    }
   ],
   "source": [
    "# load edges in order 'cited-paper' <- 'citing-paper'\n",
    "cora_location = os.path.join(dataset.data_directory, \"cora.cites\")\n",
    "g_nx = nx.read_edgelist(path=cora_location, create_using=nx.DiGraph()).reverse()\n",
    "\n",
    "# convert to undirected graph\n",
    "g_nx = g_nx.to_undirected()\n",
    "\n",
    "# load the node attribute data\n",
    "cora_data_location = os.path.join(dataset.data_directory, \"cora.content\")\n",
    "node_attr = pd.read_csv(cora_data_location, sep=\"\\t\", header=None)\n",
    "values = {str(row.tolist()[0]): row.tolist()[-1] for _, row in node_attr.iterrows()}\n",
    "nx.set_node_attributes(g_nx, values, \"subject\")\n",
    "\n",
    "# Select the largest connected component. For clarity we ignore isolated\n",
    "# nodes and subgraphs; having these in the data does not prevent the\n",
    "# algorithm from running and producing valid results.\n",
    "g_nx_ccs = (g_nx.subgraph(c).copy() for c in nx.connected_components(g_nx))\n",
    "g_nx = max(g_nx_ccs, key=len)\n",
    "print(\n",
    "    \"Largest subgraph statistics: {} nodes, {} edges\".format(\n",
    "        g_nx.number_of_nodes(), g_nx.number_of_edges()\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Node2Vec algorithm\n",
    "\n",
    "The Node2Vec algorithm introduced in [[1]](#refs) is a 2-step representation learning algorithm. The two steps are,\n",
    "\n",
    "1. Use 2nd order random walks to generate sentences from a graph. A sentence is a list of node ids. The set of all sentences makes a corpus.\n",
    "\n",
    "2. The corpus is then used to learn an embedding vector for each node in the graph. Each node id is considered a unique word/token in a dictionary that has size equal to the number of nodes in the graph. The Word2Vec algorithm [[2]](#refs), is used for calculating the embedding vectors.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Corpus generation using random walks\n",
    "\n",
    "The stellargraph library provides an implementation for 2nd order random walks as required by Node2Vec. The random walks have fixed maximum length and are controlled by two parameters `p` and `q`. See [[1]](#refs) for a detailed description of these parameters. \n",
    "\n",
    "We are going to start 10 random walks from each node in the graph with a length up to 100. We set parameter `p` to 0.5 and `q` to 2.0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of random walks: 24850\n"
     ]
    }
   ],
   "source": [
    "rw = BiasedRandomWalk(StellarGraph(g_nx))\n",
    "\n",
    "walks = rw.run(\n",
    "    nodes=list(g_nx.nodes()),  # root nodes\n",
    "    length=100,  # maximum length of a random walk\n",
    "    n=10,  # number of random walks per root node\n",
    "    p=0.5,  # Defines (unormalised) probability, 1/p, of returning to source node\n",
    "    q=2.0,  # Defines (unormalised) probability, 1/q, for moving away from source node\n",
    ")\n",
    "print(\"Number of random walks: {}\".format(len(walks)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Representation Learning using Word2Vec\n",
    "\n",
    "We use the `Word2Vec` [[2]](#refs), implementation in the free Python library `Gensim` [[3]](#refs), to learn representations for each node in the graph.\n",
    "\n",
    "We set the dimensionality of the learned embedding vectors to 128 as in [[1]](#refs)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gensim.models import Word2Vec\n",
    "\n",
    "model = Word2Vec(walks, size=128, window=5, min_count=0, sg=1, workers=2, iter=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(128,)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The embedding vectors can be retrieved from model.wv using the node ID as key.\n",
    "model.wv[\"19231\"].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualise Node Embeddings\n",
    "\n",
    "We retrieve the `Word2Vec` node embeddings that are 128-dimensional vectors and then we project them down to 2 dimensions using the [t-SNE](http://scikit-learn.org/stable/modules/generated/sklearn.manifold.TSNE.html) algorithm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Retrieve node embeddings and corresponding subjects\n",
    "node_ids = model.wv.index2word  # list of node IDs\n",
    "node_embeddings = (\n",
    "    model.wv.vectors\n",
    ")  # numpy.ndarray of size number of nodes times embeddings dimensionality\n",
    "node_targets = [g_nx.nodes[node_id][\"subject\"] for node_id in node_ids]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply t-SNE transformation on node embeddings\n",
    "tsne = TSNE(n_components=2)\n",
    "node_embeddings_2d = tsne.fit_transform(node_embeddings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x155d77b38>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# draw the points\n",
    "alpha = 0.7\n",
    "label_map = {l: i for i, l in enumerate(np.unique(node_targets))}\n",
    "node_colours = [label_map[target] for target in node_targets]\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "plt.scatter(\n",
    "    node_embeddings_2d[:, 0],\n",
    "    node_embeddings_2d[:, 1],\n",
    "    c=node_colours,\n",
    "    cmap=\"jet\",\n",
    "    alpha=alpha,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Downstream task\n",
    "\n",
    "The node embeddings calculated using `Word2Vec` can be used as feature vectors in a downstream task such as node attribute inference. \n",
    "\n",
    "In this example, we will use the `Node2Vec` node embeddings to train a classifier to predict the subject of a paper in Cora."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# X will hold the 128-dimensional input features\n",
    "X = node_embeddings\n",
    "# y holds the corresponding target values\n",
    "y = np.array(node_targets)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data Splitting\n",
    "\n",
    "We split the data into train and test sets. \n",
    "\n",
    "We use 75% of the data for training and the remaining 25% for testing as a hold out test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.1, test_size=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Array shapes:\n",
      " X_train = (248, 128)\n",
      " y_train = (248,)\n",
      " X_test = (2237, 128)\n",
      " y_test = (2237,)\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    \"Array shapes:\\n X_train = {}\\n y_train = {}\\n X_test = {}\\n y_test = {}\".format(\n",
    "        X_train.shape, y_train.shape, X_test.shape, y_test.shape\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Classifier Training\n",
    "\n",
    "We train a Logistic Regression classifier on the training data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegressionCV(Cs=10, class_weight=None, cv=10, dual=False,\n",
       "                     fit_intercept=True, intercept_scaling=1.0, l1_ratios=None,\n",
       "                     max_iter=300, multi_class='ovr', n_jobs=None, penalty='l2',\n",
       "                     random_state=None, refit=True, scoring='accuracy',\n",
       "                     solver='lbfgs', tol=0.0001, verbose=False)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = LogisticRegressionCV(\n",
    "    Cs=10, cv=10, scoring=\"accuracy\", verbose=False, multi_class=\"ovr\", max_iter=300\n",
    ")\n",
    "clf.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Predict the hold out test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = clf.predict(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculate the accuracy of the classifier on the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7510058113544926"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test, y_pred)"
   ]
  }
 ],
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